Deep Reinforcement Learning Course
This course equips you with hands-on skills to implement deep reinforcement learning for robotic systems, covering environment simulation, algorithm selection, reward engineering, sensor integration, and safe deployment.
4 to 360 hours of flexible workload
certificate valid in your country
What Will I Learn?
This Deep Reinforcement Learning Course provides a practical approach to developing and implementing robust RL policies for complex robotic systems. You will create simulated environments, design rewards, select algorithms such as SAC, PPO, and TD3, and develop vision and sensor fusion systems. Learn to ensure safety, handle sim-to-real transfer, monitor metrics, and execute reliable evaluation and deployment processes from start to finish.
Elevify Advantages
Develop Skills
- Design RL tasks for robots: define states, actions, rewards, and safety.
- Build robust sim-to-real pipelines with domain randomisation and monitoring.
- Engineer rewards and penalties that drive safe, efficient robotic behaviour.
- Select and tune DRL algorithms (PPO, SAC, TD3) for stable robot control.
- Configure sensors and state fusion for reliable factory-floor perception.
Suggested Summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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